Functions to implement K Nearest Neighbor forecasting using a weighted similarity metric tailored to the problem of forecasting univariate time series where recent observations, seasonal patterns, and exogenous predictors are all relevant in predicting future observations of the series in question. For more information on the formulation of this similarity metric please see Trupiano (2021) <arXiv:2112.06266>.
Version: | 1.0.0 |
Depends: | R (≥ 2.10) |
Imports: | stats |
Suggests: | testthat (≥ 3.0.0) |
Published: | 2022-03-05 |
Author: | Matthew Trupiano |
Maintainer: | Matthew Trupiano <matthew.trupiano.professional at gmail.com> |
BugReports: | https://github.com/mtrupiano1/knnwtsim/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/mtrupiano1/knnwtsim |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | knnwtsim results |
Reference manual: | knnwtsim.pdf |
Package source: | knnwtsim_1.0.0.tar.gz |
Windows binaries: | r-devel: knnwtsim_1.0.0.zip, r-release: knnwtsim_1.0.0.zip, r-oldrel: knnwtsim_1.0.0.zip |
macOS binaries: | r-release (arm64): knnwtsim_1.0.0.tgz, r-oldrel (arm64): knnwtsim_1.0.0.tgz, r-release (x86_64): knnwtsim_1.0.0.tgz, r-oldrel (x86_64): knnwtsim_1.0.0.tgz |
Old sources: | knnwtsim archive |
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